selected publications

1. Cancers

   Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

   Liberto, Juliane M., Chen, Sheng-Yin, Shih, Ie-Ming, Wang, Tza-Huei, Wang, Tian-Li, and Pisanic, Thomas R.

   Cancers, 2022

   Abs Bib HTML

   Ovarian high-grade serous carcinoma (HGSC) has a 5-year survival rate of less than 50%, making it one of the most lethal gynecological cancers for women in the developed world today. Delayed presentation of clinical symptoms and late-stage diagnosis drive the high mortality rate of this disease. Early detection is associated with significant improvements in survival, however, screening in the general population is currently not recommended at this time due to a notable lack of sensitive and specific biomarkers for early-stage disease. In this review, we provide an overview of the current landscape of ovarian cancer diagnostics, emphasizing emerging methodologies for the non-invasive detection of HGSC.

   @article{RN74,
     author = {Liberto, Juliane M. and Chen, Sheng-Yin and Shih, Ie-Ming and Wang, Tza-Huei and Wang, Tian-Li and Pisanic, Thomas R.},
     title = {Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review},
     journal = {Cancers},
     volume = {14},
     number = {12},
     pages = {2885},
     issn = {2072-6694},
     url = {https://www.mdpi.com/2072-6694/14/12/2885},
     year = {2022},
   }

2. Clin. Epigenetics

   Leveraging locus-specific epigenetic heterogeneity to improve the performance of blood-based DNA methylation biomarkers

   Miller, Brendan F.,  Pisanic, Thomas R., Margolin, Gennady, Petrykowska, Hanna M., Athamanolap, Pornpat, Osei-Tutu, Akosua, Annunziata, Christina M., Wang, Tza-Huei, and Elnitski, Laura

   Clinical Epigenetics, 2020

   Abs Bib HTML

   Aberrant DNA methylation is commonly heralded as a promising cancer biomarker; however, its inherently stochastic nature often leads to variable methylation patterns that can complicate the use of methylation biomarkers for clinical diagnostics, particularly in dilute samples such as liquid biopsies. Here, we present a methylation density binary classifier, a statistical method for leveraging differential heterogeneous methylation to predict and optimize the performance of methylation biomarkers for clinical applications. We first developed and tested the classifier using methylation density profiles derived from reduced representation bisulfite sequencing reads of ovarian carcinoma at ZNF154, a recurrently methylated locus in multiple cancer types. We then used in silico simulations to predict the performance of the classifier in liquid biopsies and validated these predictions using quasi-digital melt curve analysis (DREAMing) of circulating cell-free DNA from individuals with versus without ovarian carcinoma. We found good agreement between predicted and observed classifier performance, and further demonstrated that implementation of this approach with ZNF154 outperformed CA-125 for use in etiologically-diverse ovarian cancer types. Our results indicate that methylation density profiles can be exploited to predict and facilitate implementation of methylation biomarkers for clinical applications, and that ZNF154 methylation shows promise as a clinically-useful biomarker for ovarian cancer.

   @article{RN44,
     author = {Miller, Brendan F. and Pisanic, Thomas R. and Margolin, Gennady and Petrykowska, Hanna M. and Athamanolap, Pornpat and Osei-Tutu, Akosua and Annunziata, Christina M. and Wang, Tza-Huei and Elnitski, Laura},
     title = {Leveraging locus-specific epigenetic heterogeneity to improve the performance of blood-based DNA methylation biomarkers},
     journal = {Clinical Epigenetics},
     volume = {12},
     doi = {10.1186/s13148-020-00939-w},
     url = {https://www.biorxiv.org/content/10.1101/579839v2},
     year = {2020},
   }

3. Clin. Cancer Res.

   Methylomic Landscapes of Ovarian Cancer Precursor Lesions

   Pisanic, Thomas R., Wang, Yeh, Sun, Hanru, Considine, Michael, Li, Lihong, Wang, Tza-Huei, Wang, Tian-Li, and Shih, Ie-Ming

   Clinical Cancer Research, 2020

   Abs Bib HTML

   Purpose: The current paradigm in the development of high-grade serous ovarian carcinoma (HGSC) proposes that the majority of HGSCs arise from precursor serous tubal intraepithelial carcinoma (STIC) lesions of the fallopian tube. Here we survey genome-wide methylation in HGSC precursor lesions to identify genomic regions that exhibit high-specificity differential hypermethylation for potential use as biomarkers for detecting STIC and HGSC at stages when curative intervention likely remains feasible.Experimental Design: We first identified quality control criteria for performing reliable methylomic analysis of DNA-limited tubal precursor lesions with the Illumina Infinium MethylationEPIC array. We then used this platform to compare genome-wide methylation among 12 STICs with paired adjacent-normal epithelia, one p53 signature lesion and two samples of concurrent HGSC. The resulting methylomic data were analyzed by unsupervised hierarchical clustering and multidimensional analysis. Regions of high-confidence STIC-specific differential hypermethylation were identified using selective bioinformatic criteria and compared with published MethylationEPIC data from 23 HGSC tumors and 11 healthy fallopian tube mucosae.Results: Unsupervised analysis showed that STICs largely clustered with HGSCs, but were clearly distinct from adjacent-normal fallopian tube epithelia. Forty-two genomic regions exhibited high-confidence STIC-specific differential hypermethylation, of which 17 (40.5%) directly overlapped with HGSC-specific differentially methylated regions. Methylation at these shared loci was able to completely distinguish STIC and HGSC samples from normal and adjacent-normal specimens.Conclusions: Our results suggest that most STICs are epigenetically similar to HGSCs and share regions of differential hypermethylation that warrant further evaluation for potential use as biomarkers for early detection of ovarian HGSC.See related commentary by Ishak and De Carvalho, p. 6083

   @article{RN50,
     author = {Pisanic, Thomas R. and Wang, Yeh and Sun, Hanru and Considine, Michael and Li, Lihong and Wang, Tza-Huei and Wang, Tian-Li and Shih, Ie-Ming},
     title = {Methylomic Landscapes of Ovarian Cancer Precursor Lesions},
     journal = {Clinical Cancer Research},
     volume = {26},
     number = {23},
     pages = {6310-6320},
     doi = {10.1158/1078-0432.Ccr-20-0270},
     year = {2020},
   }

4. Sci. Adv.

   Facile profiling of molecular heterogeneity by microfluidic digital melt

   O’Keefe, Christine M.,  Pisanic, Thomas R., Zec, Helena, Overman, Michael J., Herman, James G., and Wang, Tza-Huei

   Science Advances, 2018

   Abs Bib HTML

   This work presents a digital microfluidic platform called HYPER-Melt (high-density profiling and enumeration by melt) for highly parallelized copy-by-copy DNA molecular profiling. HYPER-Melt provides a facile means of detecting and assessing sequence variations of thousands of individual DNA molecules through digitization in a nanowell microchip array, allowing amplification and interrogation of individual template molecules by detecting HRM fluorescence changes due to sequence-dependent denaturation. As a model application, HYPER-Melt is used here for the detection and assessment of intermolecular heterogeneity of DNA methylation within the promoters of classical tumor suppressor genes. The capabilities of this platform are validated through serial dilutions of mixed epialleles, with demonstrated detection limits as low as 1 methylated variant in 2 million unmethylated templates (0.00005%) of a classic tumor suppressor gene, CDKN2A (p14ARF). The clinical potential of the platform is demonstrated using a digital assay for NDRG4, a tumor suppressor gene that is commonly methylated in colorectal cancer, in liquid biopsies of healthy and colorectal cancer patients. Overall, the platform provides the depth of information, simplicity of use, and single-molecule sensitivity necessary for rapid assessment of intermolecular variation contributing to genetic and epigenetic heterogeneity for challenging applications in embryogenesis, carcinogenesis, and rare biomarker detection.

   @article{RN39,
     author = {O’Keefe, Christine M. and Pisanic, Thomas R. and Zec, Helena and Overman, Michael J. and Herman, James G. and Wang, Tza-Huei},
     title = {Facile profiling of molecular heterogeneity by microfluidic digital melt},
     journal = {Science Advances},
     volume = {4},
     number = {9},
     pages = {eaat6459},
     doi = {10.1126/sciadv.aat6459},
     year = {2018},
   }

5. Nucleic Acids Res.

   DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies

   Pisanic II, Thomas R., Athamanolap, Pornpat, Poh, Weijie, Chen, Chen, Hulbert, Alicia, Brock, Malcolm V., Herman, James G., and Wang, Tza-Huei

   Nucleic Acids Research, 2015

   Abs Bib HTML

   Many cancers comprise heterogeneous populations of cells at primary and metastatic sites throughout the body. The presence or emergence of distinct subclones with drug-resistant genetic and epigenetic phenotypes within these populations can greatly complicate therapeutic intervention. Liquid biopsies of peripheral blood from cancer patients have been suggested as an ideal means of sampling intratumor genetic and epigenetic heterogeneity for diagnostics, monitoring and therapeutic guidance. However, current molecular diagnostic and sequencing methods are not well suited to the routine assessment of epigenetic heterogeneity in difficult samples such as liquid biopsies that contain intrinsically low fractional concentrations of circulating tumor DNA (ctDNA) and rare epigenetic subclonal populations. Here we report an alternative approach, deemed DREAMing (Discrimination of Rare EpiAlleles by Melt), which uses semi-limiting dilution and precise melt curve analysis to distinguish and enumerate individual copies of epiallelic species at single-CpG-site resolution in fractions as low as 0.005%, providing facile and inexpensive ultrasensitive assessment of locus-specific epigenetic heterogeneity directly from liquid biopsies. The technique is demonstrated here for the evaluation of epigenetic heterogeneity at p14ARF and BRCA1 gene-promoter loci in liquid biopsies obtained from patients in association with non-small cell lung cancer (NSCLC) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), respectively.

   @article{RN75,
     author = {Pisanic II, Thomas R. and Athamanolap, Pornpat and Poh, Weijie and Chen, Chen and Hulbert, Alicia and Brock, Malcolm V. and Herman, James G. and Wang, Tza-Huei},
     title = {DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies},
     journal = {Nucleic Acids Research},
     volume = {43},
     number = {22},
     pages = {e154-e154},
     issn = {0305-1048},
     doi = {10.1093/nar/gkv795},
     url = {https://doi.org/10.1093/nar/gkv795},
     year = {2015},
   }